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A Non-invasive Subtle Pulse Rate Extraction Method Based on Eulerian Video Magnification

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Advances in Computational Intelligence Systems (UKCI 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1043))

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Abstract

Measuring pulse rate by means of video recording of the wrist area is a non-invasive approach. Eulerian Video Linear Magnification (EVLM) is used in this paper to magnify, and make visible, subtle pulse-induced wrist motions. A series of experiments are conducted to investigate the performance of ELVM under various conditions, such as light intensity, background colour and a set of video recording parameters. The results show that a light intensity of around 224 to 229 lx is optimal; excess or inadequate light significantly impairs the success of amplifying the skin movement resulting from the pulse. It is demonstrated that a white background colour enables both the radial and ulnar areas to be clearly visible in the recorded video, thus improving pulse measurement. In addition, it is shown that a female’s pulse strength is approximately 40% weaker than that of a male averaged over the participants.

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Acknowledgement

We acknowledge support for this project as part of the partnership resource of the EPSRC Interdisciplinary Research Collaboration ‘SPHERE’ - a Sensor Platform for Healthcare in a Residential Environment. EPSRC grant number: EP/K031910/1.

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Authors and Affiliations

  1. Nottingham Trent University, Nottingham, NG11 8NS, UK

    Yang Wei

  2. University of Southampton, Southampton, SO17 1BJ, UK

    Nadezhda Gracheva & John Tudor

Authors
  1. Yang Wei
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  2. Nadezhda Gracheva
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  3. John Tudor
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Corresponding author

Correspondence to Yang Wei .

Editor information

Editors and Affiliations

  1. School of Computing, University of Portsmouth, Portsmouth, UK

    Zhaojie Ju

  2. Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, UK

    Longzhi Yang

  3. Bristol Robotics Laboratory, University of the West of England, Bristol, UK

    Chenguang Yang

  4. School of Computing, University of Portsmouth, Portsmouth, Hampshire, UK

    Alexander Gegov

  5. School of Computing, University of Portsmouth, Portsmouth, UK

    Dalin Zhou

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Wei, Y., Gracheva, N., Tudor, J. (2020). A Non-invasive Subtle Pulse Rate Extraction Method Based on Eulerian Video Magnification. In: Ju, Z., Yang, L., Yang, C., Gegov, A., Zhou, D. (eds) Advances in Computational Intelligence Systems. UKCI 2019. Advances in Intelligent Systems and Computing, vol 1043. Springer, Cham. https://doi.org/10.1007/978-3-030-29933-0_38

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